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There, engineers are doing something strange. They’re freezing computer chips to 460 degrees Fahrenheit below zero, colder than deep space, to simulate the quantum structure of the universe.

At such extreme temperatures these remarkable chips, called qubits, enable scientists to peer into the complex, uncertain interaction of particles at the atomic level — an unseen world in which seemingly contradictory results can exist simultaneously, a place where simply observing an interaction can change it. Or wreck it altogether.

“Quantum — it’s something weird,” said Mike Mayberry, Intel’s chief technology officer and general manager of Intel Labs.

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Quantum computing isn’t going to revolutionize AI anytime soon, according to a panel of experts in both fields.

Different worlds: Yoshua Bengio, one of the fathers of deep learning, joined quantum computing experts from IBM and MIT for a panel discussion yesterday. Participants included Peter Shor, the man behind the most famous quantum algorithm. Bengio said he was keen to explore new computer designs, and he peppered his co-panelists with questions about what a quantum computer might be capable of.

Quantum leaps: The panels quantum experts explained that while quantum computers are scaling up, it will be a while—we’re talking years here—before they could do any useful machine learning, partly because a lot of extra qubits will be needed to do the necessary error corrections. To complicate things further, it isn’t very clear what, exactly, quantum computers will be able to do better than their classical counterparts. But both Aram Harrow of MIT and IBM’s Kristian Temme said that early research on quantum machine learning is under way.

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An international team of scientists led by the University of Groningen’s Zernike Institute for Advanced Materials created quantum bits that emit photons that describe their state at wavelengths close to those used by telecom providers. These qubits are based on silicon carbide in which molybdenum impurities create color centers. The results were published in the journal npj Quantum Information on 1 October.

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While the rest of the country has been transfixed by the Brett Kavanagh confirmation drama, the White House was quietly but steadily taking major steps to secure America’s high-tech future.

The first was the release of the National Cybersecurity Strategy last week, which I discussed in a previous column. This week came the National Strategic Overview for Quantum Information Science (QIS), released by a subcommittee of the Committee on Science for the National Science and Technology Council. This document is a big win for Jacob Taylor, the White House Office of Science and Technology Policy’s point man on all things quantum, and a major win for America.

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During last September’s Ignite conference, Microsoft heavily emphasized its quantum computing efforts and launched both its Q# programming language and development kits.

This year, the focus is on other things, and the announcements about quantum are few and far between (and our understanding is that Microsoft, unlike some of its competitors, doesn’t have a working quantum computing prototype yet). It did, however, announce an addition to its Quantum Development Kit that brings a new chemical simulation library to tools for getting started with quantum computing.

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Conventional computers store information in a bit, a fundamental unit of logic that can take a value of 0 or 1. Quantum computers rely on quantum bits, also known as a “qubits,” as their fundamental building blocks. Bits in traditional computers encode a single value, either a 0 or a 1. The state of a qubit, by contrast, can simultaneously have a value of both 0 and 1. This peculiar property, a consequence of the fundamental laws of quantum physics, results in the dramatic complexity in quantum systems.

Quantum computing is a nascent and rapidly developing field that promises to use this complexity to solve problems that are difficult to tackle with conventional computers. A key challenge for computing, however, is that it requires making large numbers of qubits work together—which is difficult to accomplish while avoiding interactions with the outside environment that would rob the qubits of their quantum properties.

New research from the lab of Oskar Painter, John G Braun Professor of Applied Physics and Physics in the Division of Engineering and Applied Science, explores the use of superconducting metamaterials to overcome this challenge.

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